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Open Access
Peer-reviewed
Research Article
An interpretable machine learning model for predicting 28-day mortality in patients with sepsis-associated liver injury
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Chengli Wen ,
Contributed equally to this work with: Chengli Wen, Xu Zhang
Roles Project administration, Writing – original draft
Affiliation Department of Intensive Care Medicine, Department of Critical Care Medicine, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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Xu Zhang ,
Contributed equally to this work with: Chengli Wen, Xu Zhang
Roles Writing – original draft
Affiliation Luzhou Key Laboratory of Human Microecology and Precision Diagnosis and Treatment, Luzhou, China
⨯ - Yong Li,
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Wanmeng Xiao,
Roles Data curation
Affiliations Luzhou Key Laboratory of Human Microecology and Precision Diagnosis and Treatment, Luzhou, China, Department of Gastroenterology, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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Qinxue Hu,
Roles Resources
Affiliation Department of Intensive Care Medicine, Department of Critical Care Medicine, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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Xianying Lei,
Roles Resources
Affiliation Department of Intensive Care Medicine, Department of Critical Care Medicine, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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Tao Xu,
Roles Resources
Affiliation Department of Intensive Care Medicine, Department of Critical Care Medicine, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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Sicheng Liang,
Roles Conceptualization
Affiliations Luzhou Key Laboratory of Human Microecology and Precision Diagnosis and Treatment, Luzhou, China, Department of Gastroenterology, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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Xiaolan Gao,
Roles Resources
Affiliation Department of Intensive Care Medicine, Department of Critical Care Medicine, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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Chao Zhang,
Roles Data curation
Affiliation Luzhou Key Laboratory of Human Microecology and Precision Diagnosis and Treatment, Luzhou, China
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Zehui Yu ,
Roles Supervision, Writing – review & editing
* E-mail: yuzehui_swmu@outlook.com (ZY); lvmuhan@swmu.edu.cn (ML)
Affiliation Laboratory Animal Center, Southwest Medical University, Luzhou, China
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Muhan Lü
Roles Supervision, Writing – review & editing
* E-mail: yuzehui_swmu@outlook.com (ZY); lvmuhan@swmu.edu.cn (ML)
Affiliations Luzhou Key Laboratory of Human Microecology and Precision Diagnosis and Treatment, Luzhou, China, Department of Gastroenterology, The Affiliated Hospital, Southwest Medical University, Luzhou, China
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An interpretable machine learning model for predicting 28-day mortality in patients with sepsis-associated liver injury
- Chengli Wen,
- Xu Zhang,
- Yong Li,
- Wanmeng Xiao,
- Qinxue Hu,
- Xianying Lei,
- Tao Xu,
- Sicheng Liang,
- Xiaolan Gao,
- Chao Zhang
- Published: May 20, 2024
- https://doi.org/10.1371/journal.pone.0303469